Patient Specific Classification of Dental Root Canal and Crown Shape.
Maxime DumontJuan Carlos PrietoSerge BrossetLucia CevidanesJonas BianchiAntonio RuellasMarcela GurgelCamila MassaroAron Aliaga Del CastilloMarcos IoshidaMarilia YatabeErika BenavidesHector RiosFabiana SokiGisele NeivaJuan Fernando AristizabalDiego ReyMaria Antonia AlvarezKayvan NajarianJonathan GryakMartin StynerJean-Christophe Fillion-RobinBeatriz PaniaguaReza SoroushmehrPublished in: Shape in Medical Imaging : International Workshop, ShapeMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings (2020)
This paper proposes machine learning approaches to support dentistry researchers in the context of integrating imaging modalities to analyze the morphology of tooth crowns and roots. One of the challenges to jointly analyze crowns and roots with precision is that two different image modalities are needed. Precision in dentistry is mainly driven by dental crown surfaces characteristics, but information on tooth root shape and position is of great value for successful root canal preparation, pulp regeneration, planning of orthodontic movement, restorative and implant dentistry. An innovative approach is to use image processing and machine learning to combine crown surfaces, obtained by intraoral scanners, with three dimensional volumetric images of the jaws and teeth root canals, obtained by cone beam computed tomography. In this paper, we propose a patient specific classification of dental root canal and crown shape analysis workflow that is widely applicable.